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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Animal Production Sc...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Animal Production Science
Article . 2025 . Peer-reviewed
Data sources: Crossref
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Enhancing predictions of nitrogen excretion in beef cattle in the tropics

Authors: S. C. Valadares Filho; A. S. Brito Neto; S. S. Moreira; L. F. Prados; F. H. M. Chizzotti; L. N. Rennó;

Enhancing predictions of nitrogen excretion in beef cattle in the tropics

Abstract

Context Excreted fecal and urinary N can cause environmental contamination. Aims Our objective was to evaluate models for predicting nitrogen (N) excreted in feces (FN), urine (UN) and manure of beef cattle; and to update the Nutrient Requirements of Zebu and Crossbred Cattle Committee dataset, and develop new models for predicting FN, UN and N in manure. Methods The dataset consisted of 30 works published between 1999 and 2024, including bulls, steers and heifers, with Nellore and crossbred animals. Criteria for inclusion in the dataset included studies in which the cattle production system was designed for meat, and the availability of individual animal data for model development and evaluation. Key results To estimate FN (g/day), two equations were adjusted, a multiple regression considering nitrogen intake (NI; g/day) and bodyweight (kg) as independent variables (concordance correlation coefficient (CCC) = 0.55; root mean square error of prediction (RMSEP) = 32.8%; RMSEP:observations standard deviation ratio (RSR) = 0.96), and a simple linear regression with NI as the independent variable (CCC = 0.53; RMSEP = 33.4%; RSR = 0.97). To predict UN (g/day), an exponential model was adjusted from NI (CCC = 0.65; RMSEP = 26.1%; RSR = 0.73). Regarding N excretion in manure (g/day), an exponential model was also used with NI as a predictor variable (CCC = 0.84; RMSEP = 15.6%; RSR = 0.52). The intercept and slope of the relationship between predicted and observed values for all developed equations were similar to 0 and 1 (P ≥ 0.09). Conclusions The equations generated were robust and accurate in estimating N excretion by feedlot beef cattle. Implications These models will provide support for planning production systems and reducing N excretion into the environment.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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